humanities networked infrastructure (huni)
DESCRIPTION
Presentation by Toby Burrows and Deb Verhoeven to the Fifth National Forum of AeRO (the Australian eResearch Organization), held in Perth on 26 July 2013. The presentation gives an overview of the HuNI Project as at July 2013. Topics covered include: data ingest and alignment from 28 Australian humanities datasets; building HuNI’s discovery functionality; and designing Virtual Laboratory tools for researchers.TRANSCRIPT
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Humanities Networked Infrastructure (HuNI)
Professor Deb Verhoeven, Deakin University
Dr Toby Burrows, University of Western Australia
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VIRTUAL LABORATORIES
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• Ensure that Australian cultural datasets and the research associated with them become part of the emerging international Linked Open Data environment
• Enable research enquiries to move easily from: what is? to where is?
• Support the role of annotation and metadata in discovery of new knowledge or the means to elucidate new knowledge
• Position the idea of data as both a subject and an object of analysis in humanities
• Contribute to debates around standards for development and implementation
HuNI: BROAD BENEFITS
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• Enable humanities researchers to work with cultural datasets more efficiently and effectively, and on a larger scale;
• Encourage the systematic sharing of research data between humanities researchers (including the cultural dataset curators themselves), the community and cultural institutions;
• Encourage a greater level of cross-disciplinary and interdisciplinary research, both within the humanities and creative arts and between the humanities/creative arts and other disciplines, and the wider public;
• Support innovative methodologies such as network analysis, game theory and ‘virtual history’ that rely on large-scale datasets
HuNI: SPECIFIC BENEFITS
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1. Organizational level: aligning the goals and processes of the institutions involved
2. Semantic level: aligning the meaning of the exchanged digital resources
3. Technical level: implementing data interoperability requires both data integration and data exchange processes as well as enabling effective use of the data that becomes available
Pasquale Pagano, ‘Data Interoperability’ (GRDI2020)4. Project level: The advent of more complex ‘big humanities’
projects requires multi-disciplinary personnel, which in turn entails the management of different workflows and expectations: developing a consortial approach, arriving at a common definition of project methods, etc.
INTEROPERABILITY
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1. The PARTNERSHIPConsortium led by Deakin University• Cultural data providers (10) – project co-operators• Humanities software developer (1) – project co-
developers• eResearch organisations (2) – lead development
agencies – VeRSI and Intersect
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HuNI PARTNER DATASETS
AMHD
MAPCAARPBonzaAFIRCCircus OzAusStage
Media: film, cinema, theatre, newspapers, magazines, advertising, music, live performances
DAAOAustLitAWRADBDoS
Biographical: artists, designers, writers, significant people, scientists, Sydney demographics
EOAS
AUSTLANGMura
Indigenous languages
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Welcome to the Cinema and Audiences Research Project (CAARP) database: An online encyclopaedia of cinema-going in Australia.
DataThis site contains information on film screenings and venues in Australia. 430,137 screenings10,256 films1,978 cinemas1,649 companiesFrom 1846 to now
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• NeCTAR investment of $1.33M
• Partner contributions of $480,000
• Partner in-kind contributions amounting to >$1M
FINANCIAL COLLABORATION
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COMMUNITY BUILDING• Collated user-stories (20) • Online showcase events – next one is 4th September
2013• Link to the alpha prototype available shortly on
huni.net.au; feedback buttons• Wider beta launch at eResearch Australasia in October
2013• Stay up to date through our monthly newsletter and
blog feed• Follow us on Twitter - @HuNIVL
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Information design challenge: to use Linked Data and ontologies / vocabularies for data to be aligned and mapped.
• Reading the data: characteristics of the data determine the ontological components selected and the major entities
• Major entities identified as: people, organizations, events, relationships, places, dates, resources, and subjects
• Components from ontologies already available and being reused or considered: CIDOC-CRM, FOAF, FRBR, FRBR-OO, BibFrame and PROV-O
2. INTEGRATING MEANING
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INGESTION WORKFLOW
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HuNI ONTOLOGY March 2013
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ALIGNING ONTOLOGIES
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3. HuNI FUNCTIONALITY
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• 28 Australian datasets are being harvested for integration into HuNI
• HuNI gateway components are deployed on the NeCTAR Research Cloud. • They harvest the XML feeds and transform them for ingestion into two
HuNI data aggregates: a Solr search server and a Jena RDF Triple Store.
DATA INTEGRATION
• Live data feeds are deployed at the partner sites to expose updated partner data as XML
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TWO HuNI DATA AGGREGATESSolr aggregate RDF aggregate
28
0
7
1
4
2
1
24
0
7
1
4
2
1
6
part
ner
data
sets
part
ner
data
sets
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TECHNOLOGY STACK for VL TOOLS
• Front-end frameworks – AngularJS and Twitter Bootstrap single page Web app
• Tools hosting framework – Open Social via Apache Shindig• Back-end framework – SpringMVC via Roo• Layer integration – RESTful Web services
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A researcher with a HuNI account will be able to:• Search the HuNI data• Save their search results as a
private collection
• Refine their collection through additional searches
• Analyse and annotate their collection with their own assertions and commentary
• Export their collection for further analysis
• Publish and share their collections and analyses
TOOLS for RESEARCHERS
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Researchers will be able to:• perform a “deep search” of
the graphs in the RDF Triple Store;
• browse by high-level facets.The large-scale aggregation of Linked Data makes explicit the relationships and connections between records across all the partner datasets, enabling the researcher to construct more complex semantic queries.
TOOLS for RESEARCHERS (2)
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RESEARCHER WORKFLOW: Discovery (part 1)
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VIRTUAL LABORATORY RESEARCHER WORKFLOW: Discovery (part 2)
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VIRTUAL LABORATORY RESEARCHER WORKFLOW: Discovery (part 3)
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VIRTUAL LABORATORY RESEARCHER WORKFLOW: Analysis (part 1)
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VIRTUAL LABORATORY RESEARCHER WORKFLOW – Analysis (part 2)
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VIRTUAL LABORATORY RESEARCHER WORKFLOW: Sharing
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VL PROTOTYPE
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4. The PROJECTHuNI staff:• project director/community liaison (20%)• project manager (100%)• technical coordinator (100%)• information services coordinator (90%)• community engagement (30%)• communication coordinator (20%)• administrative support (20%)• software developer(s)
NeCTAR Directorate
HuNI Steering
Committee
Team HuNI
Technical Working
Group
Expert Advisory
GroupExpert Data
Group
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WEB SITE: huni.net.au
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WIKI: apidictor.huni.net.au